sample of publications

• articles 

  • Clustering and forecasting of day-ahead electricity supply curves using a market-based distance.  International Journal of Electrical Power and Energy Systems.  158. 2024
  • Clustering Electricity Consumers: Challenges and Applications for Operating Smart Grids.  IEEE Power & Energy Magazine.  20:54-63. 2022
  • Cophenetic-based fuzzy clustering of time series by linear dependency.  INTERNATIONAL JOURNAL OF APPROXIMATE REASONING.  137:114-136. 2021
  • A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series.  Energies.  13:5328. 2020
  • Adaptive EWMA-S2 control charts with adaptive smoothing parameter.  Quality Engineering.  33:100-112. 2020
  • A robust procedure to build dynamic factor models with cluster structure.  Journal of Econometrics.  216:35-52. 2020
  • Hierarchical clustering for smart meter electricity loads based on quantile autocovariances.  IEEE Transactions on Smart Grid.  11:4522-4530. 2020
  • Clustering time series by linear dependency.  STATISTICS AND COMPUTING.  29:655-676. 2019
  • D-trace estimation of a precision matrix using adaptive Lasso penalties.  Advances in Data Analysis and Classification.  12:425-447. 2018
  • Forecasting financial short time series.  Electronic Journal of Applied Statistical Analysis.  11:42-57. 2018
  • Bias correction for time series factor models.  JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION.  88:1576-1602. 2018
  • Adaptive EWMA control charts with time-varying smoothing parameter.  INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY.  93:3847-3858. 2017
  • Improving the Graphical Lasso Estimation for the Precision Matrix Through Roots of the Sample Covariance Matrix.  JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS.  26:865-872. 2017
  • Fuzzy clustering of time series using extremes.  FUZZY SETS AND SYSTEMS.  318:56-79. 2017
  • Electricity price forecasting by averaging dynamic factor models.  Energies.  9:1-21. 2016
  • Clustering seasonal time series using extreme value analysis: an application to Spanish temperature time series.  Communications in Statistics - Case Studies and Data Analysis.  1:175-191. 2016
  • Wavelet-Based Clustering of Sea Level Records.  Mathematical Geosciences.  48:149-162. 2016
  • Wavelets-based clustering of air quality monitoring sites.  ENVIRONMENTAL MONITORING AND ASSESSMENT.  187. 2015
  • Forecasting mortality rates: Mexico 2001-2010.  Communications in Statistics - Case Studies and Data Analysis.  1:22-38. 2015
  • Robust functional supervised classification for time series.  JOURNAL OF CLASSIFICATION.  31:325-350. 2014
  • Overview of object oriented data analysis.  BIOMETRICAL JOURNAL.  56:732-753. 2014
  • Rejoinder to the discussion of: Overview of object-oriented data analysis.  BIOMETRICAL JOURNAL.  56:790-791. 2014
  • Comparing generalized Pareto models fitted to extreme observations: an application to the largest temperatures in Spain.  STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT.  28:1221-1233. 2014
  • Discriminant analysis of multivariate time series: application to diagnosis based on ECG signals.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  70:67-87. 2014
  • A single-index model procedure for interpolation intervals in time series.  COMPUTATIONAL STATISTICS.  28:1463-1484. 2013
  • Extreme-based clustering of environmental time series.  Boletin de Estadistica e Investigacion Operativa (Boletin de Estadistica e Investigacion Operativa).  29:92-102. 2013
  • Prediccion de clusters de series temporales demográficas.  MedULA.  22:25-28. 2013
  • Trends in ozone concentrations in the Iberian Peninsula by quantile regression and clustering.  ATMOSPHERIC ENVIRONMENT.  56:184-193. 2012
  • Supervised classification for functional data: a weighted distance approach.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  56:2334-2346. 2012
  • Extreme value and cluster analysis of European daily temperature series.  JOURNAL OF APPLIED STATISTICS.  38:2793-2804. 2011
  • Summarising changes in air temperature over Central Europe by quantile regression and clustering.  NATURAL HAZARDS AND EARTH SYSTEM SCIENCES.  11:3227-3233. 2011
  • Non-Linear Time Series Clustering based on Non-Parametric Forecast Densities.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  54:2850-2865. 2010
  • Clustering Time Series of Sea Levels: Extreme Value Approach.  JOURNAL OF WATERWAY PORT COASTAL AND OCEAN ENGINEERING.  136:215-225. 2010
  • Model-Based Clustering of Baltic Sea-Level.  APPLIED OCEAN RESEARCH.  31:4-11. 2009
  • A Time Series Bootstrap Procedure for Interpolation Intervals.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  52:1792-1805. 2008

• book chapters 

  • Model-Based Clustering of Extreme Sea Level Heights. In: Sea Level Rise, Coastal Engineering, Shorelines and Tides.  NOVA SCIENCE PUBLISHERS INC. 277-294. 2011

• books 

  • Predicción de tablas de mortalidad dinámicas mediante un procedimiento bootstrap.  MAJADAHONDA: Fundacion MAPFRE. 2008

• conference contributions 

  • Modelling multiple seasonalities of NO2 hourly pollution levels.  57. 2022
  • Predicción y clasificación basada en distancias parcialmente observadas: aplicaciones al mercado eléctrico 2020
  • Clustering time series by dependence measures 2017
  • A procedure for clustering time series 2016
  • Improving the graphical lasso estimation for the precision matrix though roots of the sample covariance matrix 2014
  • Comparing generalized pareto models fitted to extreme observation: an application to the largest temperatures in Spain 2013
  • A Single Index Model Procedure for Interpolation Intervals in Time Series 2012
  • Model Averaging in Dynamic Factor Models: An Application to Electricity Prices Forecasting 2012
  • Robust Functional Classification for Time Series 2012
  • Robust Functional Classification for Time Series 2011
  • Robust Functional Classification for Time Series 2011
  • Time Series Classification 2011
  • Clasificación de series temporales mediante análisis de datos funcionales: una aplicación en Geología.  72-72. 2010
  • A Functional Data Approach for Discrimination of Times Series 2008
  • Nonlinear Time Series Clustering Based On Nonparametric Forecast Densities 2008
  • Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting 2008

• working papers 

  • Clustering and forecasting of day-ahead electricity supply curves using a market-based distance 2024
  • BIAS correction for dynamic factor models 2017
  • Electricity prices forecasting by averaging dynamic factor models 2017
  • Monitoring variance by EWMA charts with time varying smoothing parameter 2016
  • D-trace Precision Matrix Estimation Using Adaptive Lasso Penalties 2015
  • Improving the graphical lasso estimation for the precision matrix through roots ot the sample convariance matrix 2014
  • Discriminant analysis of multivariate time series using wavelets 2012
  • Classification of Functional Data: A Weighted Distance Approach 2009
  • A Methodology for Population Projections: An Application to Spain 2008
  • Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting 2008
  • A Functional Data Based Method for Time Series Classification 2008